def main():
parser = argparse.ArgumentParser()
parser.add_argument('-m', '-M', required=True,
help='Message file')
parser.add_argument('-p', '-P', action='store_true')
parser.add_argument('-s', '-S', required=True,
help='filename to store polarity in, no extension needed')
parser.add_argument('-f', '-F', required=True,
help='folder to store the files in, ending with /')
parser.add_argument('-n', '-N', required=False, nargs=2, type=int, default=[0, 2],
help='the neutral threshold, first value is min, second is max')
args = parser.parse_args()
messagefile = args.m
location_to_store = args.f
file_to_store = args.s
separate_sentiment = args.p
neutral_limit = args.n
message_data = hlp.readcsv(messagefile)
message_header = message_data[0]
message_data = message_data[1:]
afinn = afinnsenti(data=message_data, neutral_threshold=neutral_limit)
data = afinn.compilesentiment(separate_sentiment_list=separate_sentiment, field_no=nd.m_content)
if(separate_sentiment):
hlp.dumpvariable(data, file_to_store+'.list', location_to_store)
else:
message_header.append('score')
message_header.append('label')
final_data = [message_header] + data
hlp.writecsv(final_data, location_to_store + file_to_store + '.csv', delimiter_sym=',')
def __get_top_word_sentiment(top_words):
afinn = afinnsenti()
word_senti_count = []
for (word, count) in top_words:
polarity = afinn.get_sentiment_label(word)
if -1 == polarity:
word_senti_count.append((word, 'N', count))
elif 1 == polarity:
word_senti_count.append((word, 'P', count))
elif 0 == polarity:
word_senti_count.append((word, 'U', count))
return word_senti_count
